Systems and methods for capturing and offloading different information based on event trigger type

ABSTRACT

This disclosure relates to a system and method for detecting vehicle events. The system includes sensors configured to generate output signals conveying information related to the vehicle. The system detects a vehicle event based on the information conveyed by the output signals. The system selects a subset of sensors based on the detected vehicle event. The system captures and records information from the selected subset of sensors. The system transfers the recorded information to a remote server or provider.

FIELD

The systems and methods disclosed herein are related to detection ofvehicle events, and, in particular, capturing and offloading eventrecords for detected vehicle events from particular subsets of thesensors of a vehicle.

BACKGROUND

Systems configured to record, store, and transmit video, audio, andsensor data associated with a vehicle responsive to an accidentinvolving the vehicle are known. Typically, such systems detect anaccident based on data from a single sensor such as an accelerometer.Video from the accident may usually be analyzed by a user after theaccident. Vehicle Engine Control Component (ECM) systems are known. Suchsystems interface/interoperate with external computers (e.g., at anautomobile mechanic) where the data stored by the ECM system isanalyzed.

SUMMARY

One aspect of the disclosure relates to a system configured to detectvehicle events. The system may be coupled and/or otherwise related to avehicle. Some or all of the system may be installed in the vehicleand/or be otherwise coupled with the vehicle. The system may beconfigured to capture information based on vehicle events. The systemmay be configured to off-load and/or otherwise transmit capturedinformation. In some implementations, the system may include sensors,one or more servers, one or more physical processors, electronicstorage, one or more external providers, and/or other components. Thesensors may be configured to generate output signals conveyinginformation related to the vehicle and/or one or more current operatingconditions of the vehicle. In some implementations, the system maydetect vehicle events based on a comparison of the information conveyedby the output signals from the sensors to predetermined (variable and/orfixed) values, threshold, functions, and/or other information.Advantageously, the system may identify vehicle events in real-time ornear real-time during operation of the vehicle. As used herein, the term“processor” is used interchangeably with the term “physical processor.”

The sensors may be configured to generate output signals conveyinginformation related to the operation and/or one or more operatingconditions of the vehicle. Information related to the operation of thevehicle may include feedback information from one or more of themechanical systems of the vehicle, and/or other information. In someimplementations, at least one of the sensors may be a vehicle systemsensor included in an engine control module (ECM) system or anelectronic control module (ECM) system of the vehicle. In someimplementations, one or more sensors may be carried by the vehicle. Thesensors of a particular vehicle may be referred to as a set of sensors.

Individual sensors may be configured to generate output signalsconveying information. The information may include visual information,motion-related information, position-related information, biometricinformation, and/or other information. In some implementations, thesystem may determine one or more parameters that are measured, derived,estimated, approximated, and/or otherwise determined based on one ormore output signals generated by one or more sensors.

Sensors may include, by way of non-limiting example, one or more of analtimeter (e.g. a sonic altimeter, a radar altimeter, and/or other typesof altimeters), a barometer, a magnetometer, a pressure sensor (e.g. astatic pressure sensor, a dynamic pressure sensor, a pitot sensor,etc.), a thermometer, an accelerometer, a gyroscope, an inertialmeasurement sensor, global positioning system sensors, a tilt sensor, amotion sensor, a vibration sensor, an image sensor, a camera, anultrasonic sensor, an infrared sensor, a light sensor, a microphone, anair speed sensor, a ground speed sensor, an altitude sensor, medicalsensors (including but not limited to blood pressure sensor, pulseoximeter, heart rate sensor, etc.), degree-of-freedom sensors (e.g.6-DOF and/or 9-DOF sensors), a compass, and/or other sensors. As usedherein, the term “motion sensor” may include one or more sensorsconfigured to generate output conveying information related to position,location, distance, motion, movement, acceleration, and/or othermotion-based parameters. Output signals generated by individual sensors(and/or information based thereon) may be stored and/or transferred inelectronic files.

Individual sensors may include image sensors, cameras, depth sensors,remote sensors, and/or other sensors. As used herein, the terms “camera”and/or “image sensor” may include any device that captures images,including but not limited to a single lens-based camera, a camera array,a solid-state camera, a mechanical camera, a digital camera, an imagesensor, a depth sensor, a remote sensor, a lidar, an infrared sensor, a(monochrome) complementary metal-oxide-semiconductor (CMOS) sensor, anactive pixel sensor, and/or other sensors. Individual sensors may beconfigured to capture information, including but not limited to visualinformation, video information, audio information, geolocationinformation, orientation and/or motion information, depth information,and/or other information. Information captured by one or more sensorsmay be marked, timestamped, annotated, and/or otherwise processed suchthat information captured by other sensors can be synchronized, aligned,annotated, and/or otherwise associated therewith. For example, videoinformation captured by an image sensor may be synchronized withinformation captured by an accelerometer or other sensor. Output signalsgenerated by individual image sensors (and/or information based thereon)may be stored and/or transferred in electronic files.

In some implementations, an image sensor may be integrated withelectronic storage such that captured information may be stored in theintegrated embedded storage. In some implementations, the system mayinclude one or more cameras. For example, a camera may include one ormore image sensors and electronic storage media. In someimplementations, an image sensor may be configured to transfer capturedinformation to remote electronic storage media, e.g. through “thecloud.”

The one or more servers may include one or more processors configured toexecute one or more computer program components. The computer programcomponents may include one or more of a parameter determinationcomponent, a context component, a detection component, a sensorselection component, a record component, a notification component, alocation component, and/or other components.

The parameter determination component may be configured to determinecurrent operating conditions and/or vehicle parameters. The parameterdetermination component may determine current operating conditionsand/or vehicle parameters based on the information conveyed by theoutput signals from the sensors and/or other information. The one ormore current operating conditions may be related to the vehicle, theoperation of the vehicle, physical characteristics of the vehicle,and/or other information. In some implementations, the parameterdetermination component may be configured to determine one or more ofthe current operating conditions one or more times in an ongoing mannerduring operation of the vehicle. In some implementations, the parameterdetermination component may be configured to determine one or more ofthe parameters one or more times in an ongoing manner during operationof the vehicle.

The context component may be configured to obtain, receive, and/ordetermine contextual information related to environmental conditionsnear and/or around vehicles. Environmental conditions may be related toweather conditions, road surface conditions, traffic conditions,visibility, and/or other environmental conditions. In someimplementations, one or more environmental conditions may be receivedfrom one or more sources external to the vehicle. For example, a sourceexternal to the vehicle may include a remote server and/or an externalprovider.

The detection component may be configured to detect vehicle events.Detection of vehicle events may be based on one or more currentoperating conditions of the vehicle. Detection of vehicle events may bebased on one or more parameters of the vehicle. In some implementations,detection of a vehicle event includes determination of one or more eventtypes for the detected vehicle event.

In some implementations, detection may be further based on one or moretypes of contextual information. In some implementations, detection maybe accomplished and/or performed at the vehicle, e.g. by a physicalprocessor that is carried by the vehicle.

The sensor selection component may be configured to select a subset ofsensors. Selection may be based on and/or responsive to one or both of adetection of a vehicle event and one or more particular event types fora vehicle event. Selection of a subset may include one or more sensorsfrom the set of sensors of a particular vehicle, and exclude one or moresensors from the set of sensors of a particular vehicle. In other words,a subset includes fewer sensors than the (entire or full) set of sensorsof a vehicle.

The record component may be configured to capture, record, store, and/ortransmit information, including but not limited to information relatedto vehicle events. In some implementations, information related tovehicle events may be used to create vehicle event records. Vehicleevent records may include video information, audio information, datafrom an ECM system, metadata, information based on sensor-generatedoutput, and/or other information. In some implementations, the recordcomponent may be configured to capture, record, store, and/or transmitinformation from a subset of sensors. For example, the subset of sensorsmay be selected by the sensor selection component.

Vehicle event records may be stored locally in a vehicle and/ortransmitted from a vehicle to a system, server, and/or a service that isexternal to the vehicle, including but not limited to a remote serverand/or an external provider. In some implementations, a system, server,and/or a service that is external to the vehicle may query and/orrequest information from a particular vehicle. The record component maybe configured to respond to a query or request by transmittinginformation as queried and/or requested. In some implementations, therecord component may be configured to facilitate communication ofinformation between vehicles, remote servers, external providers, and/orother systems, servers, and/or services external to vehicles.Communication may be in real-time or near real-time. Communication maybe wireless.

The notification component may be configured to generate and/ordetermine notifications related to vehicle events. In someimplementations, notifications may be intended for drivers of vehicles.For example, the notification component may be configured to providenotifications to drivers, including but not limited to warnings orrequests (for example to reduce speed). In some implementations,notifications may be transmitted from a vehicle to a system, server,and/or a service that is external to the vehicle, including but notlimited to a remote server and/or an external provider.

The location component may be configured to obtain and/or determineinformation related to the locations of vehicles and/or other locations(which may be referred to as location information). In someimplementations, the location component may be configured to receiveinformation related to the current location of a vehicle. By way ofnon-limiting example, location information may include globalpositioning system (GPS) information.

As used herein, any association (or relation, or reflection, orindication, or correspondency) involving vehicles, sensors, vehicleevents, operating conditions, parameters, thresholds, functions,notifications, and/or another entity or object that interacts with anypart of the system and/or plays a part in the operation of the system,may be a one-to-one association, a one-to-many association, amany-to-one association, and/or a many-to-many association or N-to-Massociation (note that N and M may be different numbers greater than 1).

As used herein, the term “obtain” (and derivatives thereof) may includeactive and/or passive retrieval, determination, derivation, transfer,upload, download, submission, and/or exchange of information, and/or anycombination thereof. As used herein, the term “effectuate” (andderivatives thereof) may include active and/or passive causation of anyeffect. As used herein, the term “determine” (and derivatives thereof)may include measure, calculate, compute, estimate, approximate,generate, and/or otherwise derive, and/or any combination thereof.

These and other objects, features, and characteristics of the servers,systems, and/or methods disclosed herein, as well as the methods ofoperation and functions of the related elements of structure and thecombination of parts and economies of manufacture, will become moreapparent upon consideration of the following description and theappended claims with reference to the accompanying drawings, all ofwhich form a part of this disclosure, wherein like reference numeralsdesignate corresponding parts in the various figures. It is to beexpressly understood, however, that the drawings are for the purpose ofillustration and description only and are not intended as a definitionof the limits of the invention. As used in the specification and in theclaims, the singular form of “a”, “an”, and “the” include pluralreferents unless the context clearly dictates otherwise.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system configured to capture information based ondetected vehicle events, in accordance with one or more embodiments.

FIG. 2 illustrates a method to capture information based on detectedvehicle events, in accordance with one or more embodiments.

FIG. 3 illustrates an exemplary vehicle that includes multiple sensors.

DETAILED DESCRIPTION

FIG. 1 illustrates a system 10 configured to detect vehicle events of avehicle 12. Some or all of system 10 may be installed in vehicle 12,carried by vehicle 12, and/or be otherwise coupled with and/or relatedto vehicle 12. In some implementations, system 10 may include sensors142, one or more servers 11, one or more physical processors 110,electronic storage 60, a network 13, one or more external providers 18,and/or other components. One or more sensors 142 may be configured togenerate output signals. The output signals may convey informationrelated to vehicle 12, parameters of vehicle 12, and/or currentoperating conditions of vehicle 12.

Information related to current operating conditions of the vehicle mayinclude feedback information from one or more of the mechanical systemsof vehicle 12, and/or other information. The mechanical systems ofvehicle 12 may include, for example, the engine, the drive train, thelighting systems (e.g., headlights, brake lights), the braking system,the transmission, fuel delivery systems, and/or other mechanicalsystems. The mechanical systems of vehicle 12 may include one or moremechanical sensors, electronic sensors, and/or other sensors thatgenerate the output signals (e.g., seat belt sensors, tire pressuresensors, etc.). In some implementations, at least one of sensors 142 maybe a vehicle system sensor included in an ECM system of vehicle 12.

In some implementations, sensors 142 may include one or more videocameras, one or more image sensors, and/or one or more microphones,and/or other sensors. Based on an analysis of images and/or soundscaptured, system 10 may determine, using algorithms, that vehicle 12 ismoving forward, is in reverse, has maneuvered outside of its lane oftraffic, is making a turn, and/or other maneuvers. For example, by wayof non-limiting example, driving maneuvers may include swerving, aU-turn, freewheeling, over-revving, lane-departure, short followingdistance, imminent collision, unsafe turning that approaches rolloverand/or vehicle stability limits, hard braking, rapid acceleration,idling, driving outside a geo-fence boundary, crossing double-yellowlines, passing on single-lane roads, a certain number of lane changeswithin a certain amount of time or distance, fast lane change, cuttingoff other vehicles during lane-change speeding, running a red light,running a stop sign, and/or other driving maneuvers.

In some implementations, information related to current operatingconditions of vehicle 12 may include information related to theenvironment in and/or around vehicle 12. The vehicle environment mayinclude spaces in and around an interior and an exterior of vehicle 12.The information may include information related to movement of vehicle12, an orientation of vehicle 12, a geographic position of vehicle 12, aspatial position of vehicle 12 relative to other objects, a tilt angleof vehicle 12, an inclination/declination angle of vehicle 12, and/orother information. In some implementations, the output signals conveyinginformation may be generated via non-standard aftermarket sensorsinstalled in vehicle 12. Non-standard aftermarket sensors may include,for example, a video camera, a microphone, an accelerometer, agyroscope, a geolocation sensor (e.g., a GPS device), a radar detector,a magnetometer, radar (e.g. for measuring distance of leading vehicle),and/or other sensors. In some implementations, sensors 142 may includemultiple cameras positioned around vehicle 12 and synchronized togetherto provide a 360 degree view of the inside of vehicle 12 and/or a 360degree view of the outside of vehicle 12.

Although sensors 142 are depicted in FIG. 1 as four elements, this isnot intended to be limiting. Sensors 142 may include one or more sensorslocated adjacent to and/or in communication with the various mechanicalsystems of vehicle 12, in one or more positions (e.g., at or near thefront of vehicle 12, at or near the back of vehicle 12, on the side ofvehicle 12, on or near the windshield of vehicle 12, facing outwardand/or inward, etc.) to accurately acquire information representing thevehicle environment (e.g. visual information, spatial information,orientation information), and/or in other locations. For example, insome implementations, system 10 may be configured such that a firstsensor is located near or in communication with a rotating tire ofvehicle 12, and a second sensor located on top of vehicle 12 is incommunication with a geolocation satellite. In some implementations,sensors 142 may be configured to generate output signals continuouslyduring operation of vehicle 12.

As shown in FIG. 1, server 11 may include one or more processors 110configured to execute one or more computer program components. Thecomputer program components may comprise one or more of a parameterdetermination component 21, a context component 22, a detectioncomponent 23, a sensor selection component 24, a record component 25, anotification component 26, a location component 27, and/or othercomponents.

Parameter determination component 21 may be configured to determinecurrent operating conditions and/or vehicle parameters of vehicles, e.g.vehicle 12. Parameter determination component 21 may determine currentoperating conditions and/or vehicle parameters based on the informationconveyed by the output signals from sensors 142 and/or otherinformation. The one or more current operating conditions may be relatedto vehicle 12, the operation of vehicle 12, physical characteristics ofvehicle 12, and/or other information. In some implementations, parameterdetermination component 21 may be configured to determine one or more ofthe current operating conditions and/or the vehicle parameters one ormore times in an ongoing manner during operation of vehicle 12.

In some implementations, operating conditions may include vehicleparameters. For example, vehicle parameters may be related to one ormore of an acceleration, a direction of travel, a turn diameter, avehicle speed, an engine speed (e.g. RPM), a duration of time, a closingdistance, a lane departure from an intended travelling lane of thevehicle, a following distance, physical characteristics of vehicle 12(such as mass and/or number of axles, for example), a tilt angle ofvehicle 12, an inclination/declination angle of vehicle 12, and/or otherparameters.

The physical characteristics of vehicle 12 may be physical features ofvehicle 12 set during manufacture of vehicle 12, during loading ofvehicle 12, and/or at other times. For example, the one or more vehicleparameters may include a vehicle type (e.g., a car, a bus, a semi-truck,a tanker truck), a vehicle size (e.g., length), a vehicle weight (e.g.,including cargo and/or without cargo), a number of gears, a number ofaxles, a type of load carried by vehicle 12 (e.g., food items,livestock, construction materials, hazardous materials, an oversizedload, a liquid), vehicle trailer type, trailer length, trailer weight,trailer height, a number of axles, and/or other physical features.

In some implementations, parameter determination component 21 may beconfigured to determine one or more vehicle parameters based on theoutput signals from at least two different sensors. For example,parameter determination component 21 may determine one or more of thevehicle parameters based on output signals from a sensor 142 related tothe ECM system and an external aftermarket added sensor 142. In someimplementations, a determination of one or more of the vehicleparameters based on output signals from at least two different sensors142 may be more accurate and/or precise than a determination based onthe output signals from only one sensor 142. For example, on an icysurface, output signals from an accelerometer may not convey that adriver of vehicle 12 is applying the brakes of vehicle 12. However, asensor in communication with the braking system of vehicle 12 wouldconvey that the driver is applying the brakes. System 10 may determine avalue of a braking parameter based on the braking sensor informationeven though the output signals from the accelerometer may not conveythat the driver is applying the brakes.

Parameter determination component 21 may be configured to determinevehicle parameters that are not directly measurable by any of theavailable sensors. For example, an inclinometer may not be available tomeasure the road grade, but vehicle speed data as measured by a GPSsystem and/or by a wheel sensor ECM may be combined with accelerometerdata to determine the road grade. If an accelerometer measures a forcethat is consistent with braking, but the vehicle speed remains constant,the parameter component can determine that the measured force is acomponent of the gravity vector that is acting along the longitudinalaxis of the vehicle. By using trigonometry, the magnitude of the gravityvector component can be used to determine the road grade (e.g., pitchangle of the vehicle in respect to the horizontal plane).

In some implementations, one or more of the vehicle parameters may bedetermined one or more times in an ongoing manner during operation ofvehicle 12. In some implementations, one or more of the vehicleparameters may be determined at regular time intervals during operationof vehicle 12. The timing of the vehicle parameter determinations (e.g.,in an ongoing manner, at regular time intervals, etc.) may be programmedat manufacture, obtained responsive to user entry and/or selection oftiming information via a user interface and/or a remote computingdevice, and/or may be determined in other ways. The time intervals ofparameter determination may be significantly less (e.g. more frequent)than the time intervals at which various sensor measurements areavailable. In such cases, system 10 may estimate vehicle parameters inbetween the actual measurements of the same vehicle parameters by therespective sensors, to the extent that the vehicle parameters aremeasurable. This may be established by means of a physical model thatdescribes the behavior of various vehicle parameters and theirinterdependency. For example, a vehicle speed parameter may be estimatedat a rate of 20 times per second, although the underlying speedmeasurements are much less frequent (e.g., four times per second for ECMspeed, one time per second for GPS speed). This may be accomplished byintegrating vehicle acceleration, as measured by the accelerometersensor where the measurements are available 1000 times per second,across time to determine change in speed that is accumulated over timeagain for the most recent vehicle speed measurement. The benefit ofthese more frequent estimates of vehicle parameters are many and theyinclude improved operation of other components of system 10, reducedcomplexity of downstream logic and system design (e.g., all vehicleparameters are updated at the same interval, rather than being updatingirregularly and at the interval of each respective sensor), and morepleasing (e.g., “smooth”) presentation of vehicle event recorder datathrough an event player apparatus.

In some implementations, system 10 may be configured to detect specificdriving maneuvers based on one or more of a vehicle speed, an engineload, a throttle level, an accelerator position, vehicle direction, agravitational force, and/or other parameters being sustained at or abovethreshold levels for pre-determined amounts of time. In someimplementations, an acceleration and/or force threshold may be scaledbased on a length of time an acceleration and/or force is maintained,and/or the particular speed the vehicle is travelling. System 10 may beconfigured such that force maintained over a period of time at aparticular vehicle speed may decrease a threshold force the longer thatthe force is maintained. System 10 may be configured such that, combinedwith engine load data, throttle data may be used to determine a riskyevent, a fuel wasting event, and/or other events.

Context component 22 may be configured to obtain, receive, and/ordetermine contextual information related to environmental conditionsnear and/or around vehicles. Environmental conditions may be related toweather conditions, road surface conditions, traffic conditions,visibility, and/or other environmental conditions. In someimplementations, environmental conditions may be related to proximity ofcertain objects that are relevant to driving, including but not limitedto traffic signs, railroad crossings, time of day, ambient lightconditions, altitude, and/or other objects relevant to driving. In someimplementations, one or more environmental conditions may be receivedfrom one or more sources external to vehicle 12. For example, a sourceexternal to vehicle 12 may include a remote server and/or an externalprovider 18. In some implementations, contextual information may includea likelihood of traffic congestion near a particular vehicle, and/ornear a particular location. In some implementations, contextualinformation may include a likelihood of the road surface near aparticular vehicle and/or a particular location being icy, wet, and/orotherwise potentially having an effect of braking. In someimplementations, environmental conditions may include informationrelated to a particular driver and/or a particular trip. For example,with every passing hour that a particular driver drives his vehicleduring a particular trip, the likelihood of drowsiness may increase. Insome implementations, the function between trip duration or distance andlikelihood of drowsiness may be driver-specific.

In some implementations, contextual information may be received bysystem 10 through network 13, e.g. the internet. Network 13 may includeprivate networks, public networks, and/or combinations thereof. Forexample, contextual information related to weather conditions may bereceived from a particular external provider 18 that provides weatherinformation. For example, contextual information related to road surfaceconditions may be received from a particular external provider 18 thatprovides road condition information. For example, contextual informationrelated to traffic conditions may be received from a particular externalprovider 18 that provides traffic information.

Detection component 23 may be configured to detect vehicle events.Detection of vehicle events may be based on one or more currentoperating conditions of vehicle 12. Alternatively, and/orsimultaneously, detection of vehicle events may be based on one or morevehicle parameters of vehicle 12. In some implementations, detection ofa vehicle event may include determination of one or more event types forthe detected vehicle event. For example, some vehicle events may berelated to proximity of vehicle 12 to some object in front of vehicle12. For example, some event types may be related to proximity of vehicle12 to some object in front of vehicle 12. For example, some vehicleevents may be related to proximity of vehicle 12 to some object behindvehicle 12. For example, some event types may be related to proximity ofvehicle 12 to some object behind vehicle 12. For example, some vehicleevents may be related to proximity of vehicle 12 to some object to aparticular side of vehicle 12 (e.g., the loading side, the revenue side,and/or other sides). For example, some event types may be related toproximity of vehicle 12 to some object to a particular side of vehicle12 (e.g., the loading side, the revenue side, and/or other sides). Forexample, some vehicle events may be related to the speed of vehicle 12being less than some predetermined speed threshold. For example, someevent types may be related to the speed of vehicle 12 being less thansome predetermined speed threshold. For example, some vehicle events maybe related to the speed of vehicle 12 being more than some predeterminedspeed threshold. For example, some event types may be related to thespeed of vehicle 12 being more than some predetermined speed threshold.For example, some vehicle events may be categorized as having aparticular event type based on a particular driving maneuver thatvehicle 12 is performing. For example, one or more event types may berelated to driving backwards, parking a vehicle, driving in a parkinglot or garage, being stalled at a traffic light, loading and/orunloading from the vehicle, performing some operation involving thevehicle (e.g., transferring gasoline from a tanker truck), and/or otherevents related to a vehicle.

In some implementations, detection of vehicle events and/ordetermination of event types may be further based on one or more typesof contextual information. In some implementations, detection and/ordetermination may be accomplished and/or performed at vehicle 12, e.g.by processor 110 that is carried by vehicle 12. Alternatively, and/orsimultaneously, in some implementations, detection and/or determinationmay be accomplished and/or performed remote from vehicle 12, e.g. byprocessor 110 that is not carried by vehicle 12. Vehicle events mayinclude speeding, unsafe driving speed, collisions, near-collisions,and/or other events. In some implementations, vehicle events may includethe distance between two vehicles being dangerously small, which may forexample indicate an increased likelihood of a collision. In someimplementations, vehicle events may include one or more drivingmaneuvers, e.g. in a particular predefined sequence.

In some implementations, a value of a current operating condition thateffectuates detection of a vehicle event and/or determination of anevent type may vary as a function of the contextual information. Forexample, a speed of 50 mph (in a particular geographical location) maynot effectuate detection of a vehicle event and/or determination of anevent type when the road surface is dry and/or when traffic is light,but the same speed in the same geographical location may effectuatedetection of a vehicle event and/or determination of an event typeresponsive to contextual information and/or other information indicatingthat the road surface is wet and/or icy (and/or may be wet and/or icy),or responsive to contextual information (and/or other information) thattraffic is heavy (and/or may be heavy). In this example, the contextualinformation (and/or other information) may have an effect of thedetection of vehicle events and/or the determination of event types. Insome implementations, contextual information (and/or other information)may modify the sensitivity of the process and/or mechanism by whichvehicle events are detected and/or event types are determined.

For example, a particular vehicle 12 operates at a particular operatingcondition (as determined based on output signals generated by aparticular sensor 142). In light of a particular current environmentalcondition at a first moment (e.g. sunny weather and/or light traffic),the particular operating condition may provide an insufficient impetusto determine and/or detect a particular vehicle event (e.g. “unsafedriving speed”). Subsequently, at a second moment after the firstmoment, a different environmental condition (e.g. rain, snow, and/orheavy traffic) becomes operative (e.g., the different environmentalcondition may be received at particular vehicle 12 as contextualinformation and/or other information). In light of the differentenvironmental condition, the combination of the different environmentalcondition and the particular operating condition may provide asufficient impetus to determine and/or detect a particular vehicleevent.

In some implementations, detection of vehicle events and/ordetermination of event types may be based on one or more comparisons ofthe values of current operating conditions with threshold values. Insome implementations, a particular threshold value may vary as afunction of contextual information. In some implementations, aparticular threshold value may vary as a function of other information,e.g. as determined based on sensor output.

By way of non-limiting example, lateral forces of about −0.3 g (e.g.,swerve left) and/or about +0.3 g (e.g., swerve right) may be a basisused to detect a swerve. In some implementations, the −0.3 g and/or +0.3g criteria may be used at vehicle 12 speeds less than about 10 kph. The−0.3 g and/or +0.3 g criteria may be scaled as vehicle 12 increases inspeed. In some implementations, the −0.3 g and/or +0.3 g criteria may bescaled (e.g., reduced) by about 0.0045 g per kph of speed over 10 kph.To prevent too much sensitivity, system 10 may limit the lateral forcecriteria to about +/−0.12 g, regardless of the speed of vehicle 12, forexample. In some implementations, the criterion for the given period oftime between swerves may be about 3 seconds.

Sensor selection component 24 may be configured to select a subset ofsensors. Selection may be based on and/or responsive to one or both of adetection of a vehicle event and/or one or more particular event typesfor a vehicle event. Selection of a subset may mean including one ormore sensors from the set of sensors 142 of a particular vehicle, andexcluding one or more sensors from the set of sensors of a particularvehicle. In other words, a subset may include fewer sensors than the(entire or full) set of sensors 142 of a vehicle. In someimplementations, a particular vehicle event may be associated with aparticular subset of sensors. In some implementations, a particularevent type may be associated with a particular subset of sensors. Forexample, an event type related to driving backwards may be associatedwith, at least, backward-facing video cameras. For example, an eventtype related to a swerve may be associated with, at least,sideways-facing video cameras.

Record component 25 may be configured to capture, record, store,transmit, and/or process information, including but not limited toinformation related to vehicle events. In some implementations,information related to vehicle events may be used to generate and/orcreate vehicle event records. Vehicle event records may include videoinformation, audio information, data from an ECM system, metadata,timing information, information based on sensor-generated output, and/orother information. In some implementations, the capacity to generateand/or capture new information may exceed the capacity to record, store,transmit, and/or process that information. In particular, video camerasmay generate a large amount of data. In implementations having multiplevideo cameras per vehicle, record component 25 may be configured toprocess information from fewer than the full set of sensors of vehicle12. For example, record component 25 may process information from asubset of sensors 142 of vehicle 12, e.g. as selected by sensorselection component 24.

Vehicle event records may be generated and/or stored locally in vehicle12 and/or transmitted from vehicle 12 to system 10, server 11, and/or toa service that is external to the vehicle, including but not limited toa remote server and/or external provider 18. In some implementations,vehicle event records may be generated and/or stored remotely, i.e. notlocally at vehicle 12. In some implementations, system 10, server 11,and/or a service that is external to vehicle 12 may query and/or requestinformation from a particular vehicle 12. Record component 25 may beconfigured to respond to a query or request by transmitting informationas queried and/or requested. In some implementations, record component25 may be configured to facilitate communication of information betweenparticular vehicles, remote servers, external providers, and/or othersystems, servers, and/or services external to the particular vehicles.Such communication may be in real-time or near real-time. Suchcommunication may include wireless communication.

In some implementations, system 10 may be configured to detect multipledifferent vehicle events, e.g. at different points in time. The multiplevehicle events may include a first vehicle event, second vehicle event,third vehicle event, and/or additional vehicle events. Responsive todetection of the first vehicle event, system 10 may be configured toselect a first subset of sensors 142, capture information based on thefirst subset of sensors 142, and generate a first event record thatincludes and/or is based on the captured information. Responsive todetection of the second vehicle event, system 10 may be configured toselect a second subset of sensors 142 that is different than the firstsubset of sensors, capture information based on the second subset ofsensors 142, and generate a second event record that includes and/or isbased on the captured information. At least one sensor in the firstsubset of sensor may have a different field-of-view (of an environmentin and/or around vehicle 12) than any of the sensors in the secondsubset of sensors. Responsive to detection of the third vehicle event,system 10 may be configured to select a third subset of sensors 142 thatis different than the first and second subsets of sensors, captureinformation based on the third subset of sensors 142, and generate athird event record that includes and/or is based on the capturedinformation. At least one sensor in the third subset of sensor may havea different field-of-view (of an environment in and/or around vehicle12) than any of the sensors in the first and second subsets of sensors.

In some implementations, the second subset of sensors may exclude atleast one sensor that is included in the first subset of sensors. Insome implementations, the third subset of sensors may exclude at leastone sensor that is included in either the first or second subset ofsensors.

By way of non-limiting example, FIG. 3 illustrates an exemplary vehicle12 that includes multiple sensors, labeled 142 a-142 h. For example,sensors 142 a, 142 b, 142 c, and 142 d may include wheel sensors. Forexample, sensor 142 e may include a rear-facing camera. For example,sensor 142 f may include a side-facing camera. For example, sensor 142 gmay include a forward facing-camera. For example, sensor 142 h mayinclude an inward-facing camera. In some implementations, a first subsetof sensors may include forward-facing camera 142 g but excluderear-facing camera 142 e. In some implementations, a second subset ofsensors may exclude forward-facing camera 142 g but include rear-facingcamera 142 e. In some implementations, a third subset of sensors mayinclude side-facing camera 142 f and/or inward-facing camera 142 h, butexclude one or both of forward-facing camera 142 g and rear-facingcamera 142 e. These examples are not intended to be limiting in any way.

Notification component 26 may be configured to generate and/or determinenotifications related to vehicle events. In some implementations,notifications may be intended for drivers of vehicles. For example,notification component 26 may be configured to provide notifications todrivers, including but not limited to warnings or requests (for exampleto reduce speed). In some implementations, notifications may betransmitted from vehicle 12 to system 10, server 11, and/or a servicethat is external to vehicle 12, including but not limited to a remoteserver and/or external provider 18. For example, a notification that acollision has occurred may be transmitted to a remote server and/orexternal provider 18. In some implementations, notifications may bestored locally, in electronic storage of a particular vehicle 12. Storednotifications may be retrieved later, e.g. after the particular vehicle12 has returned to fleet headquarters, or subsequent to the particularvehicle 12 entering a particular geographical area (e.g. within range ofwireless communication with a particular external provider 18).

Location component 27 may be configured to obtain and/or determineinformation related to the locations of vehicles and/or other locations(which may be referred to as location information). In someimplementations, location component 27 may be configured to receiveinformation related to the current location of vehicle 12. By way ofnon-limiting example, location information may include globalpositioning system (GPS) information. Operation by other components ofsystem 10 may be based, at least in part, on information obtained and/ordetermined by location component 27. For example, detection of vehicleevents may be affected based on proximity and/or orientation to objectsnear vehicle 12, geo-fence around vehicle 12, and/or other conditionsrelated to vehicle 12.

In some implementations, system 10 may include a user interfaceconfigured to provide an interface between system 10 and users throughwhich the users may provide information to and receive information fromsystem 10. This enables information to be communicated between a userand one or more of processor 110, sensors 142, vehicle 12, and/or othercomponents of system 10. As an example, a dangerous driving maneuverand/or vehicle event may be displayed to the driver of vehicle 12 viathe user interface, e.g. as a notification.

Examples of interface devices suitable for inclusion in a user interfaceinclude a keypad, buttons, switches, a keyboard, knobs, levers, adisplay screen, a touch screen, speakers, a microphone, an indicatorlight, an audible alarm, a printer, a tactile feedback device, and/orother interface devices.

It is to be understood that other communication techniques, eitherhard-wired or wireless, are also contemplated by the present disclosureas a user interface. Information may be loaded into system 10 wirelesslyfrom a remote location, from removable storage (e.g., a smart card, aflash drive, a removable disk, etc.), and/or other sources that enablethe user(s) to customize the implementation of system 10. Otherexemplary input devices and techniques adapted for use with system 10include, but are not limited to, an RS-232 port, RF link, an IR link,modem (telephone, cable, and/or other modems), a cellular network, aWi-Fi network, a local area network, and/or other devices and/orsystems. In short, any technique for communicating information withsystem 10 is contemplated by the present disclosure as a user interface.

Electronic storage 60 may comprise electronic storage media thatelectronically stores information. The electronic storage media ofelectronic storage 60 may comprise one or both of system storage that isprovided integrally (i.e., substantially non-removable) with system 10and/or removable storage that is removably connectable to system 10 via,for example, a port (e.g., a USB port, a firewire port, etc.) or a drive(e.g., a disk drive, etc.). Electronic storage 60 may comprise one ormore of optically readable storage media (e.g., optical disks, etc.),magnetically readable storage media (e.g., magnetic tape, magnetic harddrive, floppy drive, etc.), electrical charge-based storage media (e.g.,EEPROM, RAM, etc.), solid-state storage media (e.g., flash drive, etc.),and/or other electronically readable storage media. Electronic storage60 may store software algorithms, recorded video event data, informationdetermined by processor 110, information received via a user interface,and/or other information that enables system 10 to function properly.Electronic storage 60 may be (in whole or in part) a separate componentwithin system 10, or electronic storage 60 may be provided (in whole orin part) integrally with one or more other components of system 10.

In some implementations, a remote server may include communicationlines, or ports to enable the exchange of information with a network,processor 110 of system 10, and/or other computing platforms. The remoteserver may include a plurality of processors, electronic storage,hardware, software, and/or firmware components operating together toprovide the functionality attributed herein to a remote device. Forexample, the server may be implemented by a cloud of computing platformsoperating together as a system server.

As described above, processor 110 may be configured to provideinformation-processing capabilities in system 10. As such, processor 110may comprise one or more of a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or othermechanisms for electronically processing information. Although processor110 is shown in FIG. 1 as a single entity, this is for illustrativepurposes only. In some implementations, processor 110 may comprise aplurality of processing units. These processing units may be physicallylocated within the same device (e.g., a vehicle event recorder), orprocessor 110 may represent processing functionality of a plurality ofdevices operating in coordination.

Processor 110 may be configured to execute components 21-27 by software;hardware; firmware; some combination of software, hardware, and/orfirmware; and/or other mechanisms for configuring processingcapabilities on processor 110. It should be appreciated that althoughcomponents 21-27 are illustrated in FIG. 1 as being co-located within asingle processing unit, in implementations in which processor 110comprises multiple processing units, one or more of components 21-27 maybe located remotely from the other components. The description of thefunctionality provided by the different components 21-27 describedherein is for illustrative purposes, and is not intended to be limiting,as any of components 21-27 may provide more or less functionality thanis described. For example, one or more of components 21-27 may beeliminated, and some or all of its functionality may be provided byother components 21-27. As another example, processor 110 may beconfigured to execute one or more additional components that may performsome or all of the functionality attributed below to one of components21-27.

FIG. 2 illustrates a method 200 to capture information based on detectedvehicle events. The operations of method 200 presented below areintended to be illustrative. In some implementations, method 200 may beaccomplished with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of method 200 are illustrated (in FIG.2) and described below is not intended to be limiting. In someimplementations, two or more of the operations may occur substantiallysimultaneously.

In some implementations, method 200 may be implemented in one or moreprocessing devices (e.g., a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or othermechanisms for electronically processing information). The one or moreprocessing devices may include one or more devices executing some or allof the operations of method 200 in response to instructions storedelectronically on one or more electronic storage mediums. The one ormore processing devices may include one or more devices configuredthrough hardware, firmware, and/or software to be specifically designedfor execution of one or more of the operations of method 200.

Referring to FIG. 2 and method 200, at an operation 202, output signalsare generated that convey information related to one or more currentoperating conditions of the vehicle. In some embodiments, operation 202is performed by sensors the same as or similar to sensors 142 (shown inFIG. 1 and described herein). The set of sensors is carried by thevehicle.

At an operation 204, vehicle events are detected based on the generatedoutput signals. Detection of the vehicle events includes determinationof event type for the individual vehicle events. In some embodiments,operation 204 is performed by a detection component the same as orsimilar to detection component 23 (shown in FIG. 1 and describedherein).

At an operation 206, responsive to detection of a first vehicle event ofa first event type, and based on the first event type, a first subset ofsensors is selected. The first subset of sensors excludes at least oneof the sensors from the set of sensors. In some embodiments, operation206 is performed by a sensor selection component the same as or similarto sensor selection component 24 (shown in FIG. 1 and described herein).

At an operation 208, information is captured that is conveyed by theoutput signals that are generated by the first subset of sensorsproximate in time to the first vehicle event. In some embodiments,operation 208 is performed by a record component the same as or similarto record component 25 (shown in FIG. 1 and described herein).

At an operation 210, a first event record is generated that isassociated with the first vehicle event. The first event record includesthe captured information. In some embodiments, operation 210 isperformed by a record component the same as or similar to recordcomponent 25 (shown in FIG. 1 and described herein).

Although the system(s) and/or method(s) of this disclosure have beendescribed in detail for the purpose of illustration based on what iscurrently considered to be the most practical and preferredimplementations, it is to be understood that such detail is solely forthat purpose and that the disclosure is not limited to the disclosedimplementations, but, on the contrary, is intended to covermodifications and equivalent arrangements that are within the spirit andscope of the appended claims. For example, it is to be understood thatthe present disclosure contemplates that, to the extent possible, one ormore features of any implementation can be combined with one or morefeatures of any other implementation.

What is claimed is:
 1. A system configured to capture information basedon detected vehicle events, the system configured to couple with avehicle, the system comprising: electronic storage configured toelectronically store information, wherein the electronic storage iscarried by the vehicle; a set of sensors configured to generate outputsignals conveying information related to current operating conditions ofthe vehicle, wherein the set of sensors is carried by the vehicle; a setof cameras configured to capture image data, wherein the set of camerasis carried by the vehicle, wherein the set of cameras includes a firstcamera, a second camera, and a third camera configured to capture imagedata, and wherein the set of cameras includes at least one interiorcamera configured to capture visual information inside the vehicle; andone or more processors configured to: determine the current operatingconditions of the vehicle while the vehicle is in motion, whereindetermination is based on the generated output signals; detect vehicleevents while the vehicle is in motion based on driving maneuvers thevehicle is performing, wherein detection of the vehicle events is basedon the determined current operating conditions related to informationconveyed by the generated output signals from at least two differentsensors in the set of sensors, wherein the driving maneuvers include oneor more of swerving, a U-turn, freewheeling, over-revving,lane-departure, short following distance, imminent collision, unsafeturning that approaches rollover, hard braking, rapid acceleration,idling, driving outside a geo-fence boundary, crossing double-yellowlines, passing on single-lane roads, a certain number of lane changeswithin a certain amount of time or distance, fast lane change, cuttingoff other vehicles during lane-change speeding, running a red light,and/or running a stop sign, wherein the detected vehicle events includea first vehicle event, a second vehicle event, and a third vehicleevent; determine a first event type for the first vehicle event based ona first driving maneuver the vehicle is performing, a second event typefor the second vehicle event based on a second driving maneuver thevehicle is performing, and a third event type for the third vehicleevent based on a third driving maneuver the vehicle is performing,wherein the first, second, and third event types are different eventtypes corresponding to different driving maneuvers; responsive todetection of the first vehicle event, and based on the first event type,select a first subset of cameras from the set of cameras, wherein thefirst subset of cameras includes the first camera and excludes at leastone of the second and third cameras; responsive to detection of thesecond vehicle event, and based on the second event type, select asecond subset of cameras from the set of cameras, wherein the secondsubset of cameras includes the second camera and excludes at least oneof the first and third cameras; responsive to detection of the thirdvehicle event, and based on the third event type, select a third subsetof cameras from the set of cameras, wherein the third subset of camerasincludes the third camera and excludes at least one of the first andsecond cameras; capture first image data by the first subset of camerasproximate in time to the first vehicle event; capture second image databy the second subset of cameras proximate in time to the second vehicleevent; capture third image data by the third subset of cameras proximatein time to the third vehicle event; generate a first event recordassociated with the first vehicle event, wherein the first event recordincludes the captured first image data; generate a second event recordassociated with the second vehicle event, wherein the second eventrecord includes the captured second image data; generate a third eventrecord associated with the third vehicle event, wherein the third eventrecord includes the captured third image data; store the first, second,and third event record in the electronic storage; and transmit thefirst, second, and third event records from the electronic storage to aremote server that is external to the vehicle.
 2. The system of claim 1,the vehicle having a rear side, wherein the first event type correspondsto vehicle events at or near the rear side of the vehicle.
 3. The systemof claim 1, wherein the first event type corresponds to vehicle eventsat or near a side of the vehicle.
 4. The system of claim 1, wherein theset of sensors includes a depth sensor configured to generate outputsignals conveying depth information, the depth information includingranges of surfaces and/or objects within an environment in and/or aroundthe vehicle, the environment around the vehicle including an area withina first field-of-view of the first camera and/or a second field-of-viewof the second camera, wherein the first vehicle event is related to adistance between two vehicles, wherein detection of the first vehicleevent is based on the depth information.
 5. The system of claim 1,wherein detection of the first vehicle event is based on a comparison ofa value of a current operating condition of the vehicle with a thresholdvalue.
 6. The system of claim 1, wherein a current operating conditionof the vehicle includes one or more of an engine load, a throttle level,a particular change in vehicle direction, or multiple changes in vehicledirection.
 7. The system of claim 1, wherein the first vehicle event isrelated to unsafe vehicle speed.
 8. The system of claim 1, wherein thefirst vehicle event is an imminent collision, wherein the second vehicleevent is a swerve, wherein the first camera is a forward-facing camera,wherein the second camera is a sideways-facing camera, wherein the firstsubset of cameras excludes the sideways-facing camera, and wherein thesecond subset of cameras includes the sideways-facing camera.
 9. Thesystem of claim 1, wherein the first event type corresponds to vehicleevents occurring at a particular speed of the vehicle, wherein theparticular speed of the vehicle is less than a speed threshold, andwherein the first vehicle event occurred at a speed less than the speedthreshold.
 10. The system of claim 1, wherein the one or more processorsare further configured to obtain contextual information related toenvironmental conditions near and/or around the vehicle, wherein theenvironmental conditions include one or more of weather conditions, roadsurface conditions, and/or visibility, and wherein the vehicle eventsare further based on the obtained contextual information.
 11. The systemof claim 10, wherein detection of the first vehicle event is based on acomparison with a threshold value, wherein the threshold value used forthe detection is adjusted, and wherein adjustment of the threshold valueis based on the contextual information.
 12. The system of claim 1,wherein the one or more processors are further configured to: generatefirst, second, and third notifications related to the first, second, andthird vehicle events, respectively, and transmit the first, second, andthird notifications to the remote server; and receive, from the remoteserver, one or more requests for one or more particular event records,wherein transmission of the first, second, and third event records isresponsive to the request by the remote server requesting the first,second, and third event records, respectively.
 13. A method to captureinformation based on detected vehicle events of a vehicle, the methodcomprising: generating, by a set of sensors, output signals conveyinginformation related to current operating conditions of the vehicle,wherein the set of sensors is carried by the vehicle; capturing, by aset of cameras, image data, wherein the set of cameras includes a firstcamera, a second camera, and a third camera configured to capture imagedata, and wherein the set of cameras includes at least one interiorcamera configured to capture visual information inside the vehicle;determining the current operating conditions of the vehicle while thevehicle is in motion, wherein determination is based on the generatedoutput signals; detecting vehicle events while the vehicle is in motionbased on driving maneuvers the vehicle is performing, wherein detectionof the vehicle events is based on the determined current operatingconditions, wherein the driving maneuvers includes one or more ofswerving, a U-turn, freewheeling, over-revving, lane-departure, shortfollowing distance, imminent collision, unsafe turning that approachesrollover, hard braking, rapid acceleration, idling, driving outside ageo-fence boundary, crossing double-yellow lines, passing on single-laneroads, a certain number of lane changes within a certain amount of timeor distance, fast lane change, cutting off other vehicles duringlane-change speeding, running a red light, and/or running a stop sign,wherein the detected vehicle events include a first vehicle event, asecond vehicle event, and a third vehicle event; determining a firstevent type for the first vehicle event based on a first driving maneuverthe vehicle is performing, a second event type for the second vehicleevent based on a second driving maneuver the vehicle is performing, anda third event type for the third vehicle event based on a third drivingmaneuver the vehicle is performing, wherein the first, second, and thirdevent types are different event types corresponding to different drivingmaneuvers; responsive to detection of the first vehicle event, and basedon the first event type, selecting a first subset of cameras from theset of cameras, wherein the first subset of cameras includes the firstcamera and excludes at least one of the second and third cameras;responsive to detection of the second vehicle event, and based on thesecond event type, selecting a second subset of cameras from the set ofcameras, wherein the second subset of cameras includes the second cameraand excludes at least one of the first and third cameras; responsive todetection of the third vehicle event, and based on the third event type,selecting a third subset of cameras from the set of cameras, wherein thethird subset of cameras includes the third camera and excludes at leastone of the first and second cameras; capturing first image data by thefirst subset of cameras proximate in time to the first vehicle event;capturing second image data by the second subset of cameras proximate intime to the second vehicle event; capturing third image data by thethird subset of cameras proximate in time to the third vehicle event;generating a first event record associated with the first vehicle event,wherein the first event record includes the captured first image data;generating a second event record associated with the second vehicleevent, wherein the second event record includes the captured secondimage data; generating a third event record associated with the thirdvehicle event, wherein the third event record includes the capturedthird image data; storing the first, second, and third event records inelectronic storage, wherein the electronic storage is carried by thevehicle; and transmitting the first, second, and third event recordsfrom the electronic storage to a remote server that is external to thevehicle.
 14. The method of claim 13, the vehicle having a rear side,wherein the first event type corresponds to vehicle events at or nearthe rear side of the vehicle.
 15. The method of claim 13, wherein thefirst event type corresponds to vehicle events at or near a side of thevehicle.
 16. The method of claim 13, wherein the set of sensors includesa depth sensor configured to generate output signals conveying depthinformation, the depth information including ranges of surfaces and/orobjects within an environment in and/or around the vehicle, theenvironment around the vehicle including an area within a firstfield-of-view of the first camera and/or a second field-of-view of thesecond camera, wherein the first vehicle event is related to a distancebetween two vehicles, wherein detection of the first vehicle event isbased on the depth information.
 17. The method of claim 13, whereindetection of the first vehicle event is based on a comparison of a valueof a current operating condition of the vehicle with a threshold value.18. The method of claim 13, wherein a current operating condition of thevehicle includes one or more of an engine load, a throttle level, aparticular change in vehicle direction, or multiple changes in vehicledirection.
 19. The method of claim 13, wherein the first vehicle eventis related to unsafe vehicle speed.
 20. The method of claim 13, whereinthe first vehicle event is an imminent collision, wherein the secondvehicle event is a swerve, wherein the first camera is a forward-facingcamera, wherein the second camera is a sideways-facing camera, whereinthe first subset of cameras excludes the sideways-facing camera, andwherein the second subset of cameras includes the sideways-facingcamera.